Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved DISTRIBUTED SYSTEMS Principles and Paradigms Second Edition ANDREW S. TANENBAUM MAARTEN VAN STEEN Chapter 1 Introduction

Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved Definition of a Distributed System (1) A distributed system is: A collection of independent computers that appears to its users as a single coherent system.

Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved Definition of a Distributed System (2) Figure 1-1. A distributed system organized as middleware. The middleware layer extends over multiple machines, and offers each application the same interface.

Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved Goals of Distributed Systems  Making resources accessible  Distribution transparency  Openness  Scalability

Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved Making Resources Accessible  Making it easy for users and applications to access remote resources  Share remote resources in a controlled and efficient manner  Benefits  Better economics by sharing expensive resources  Easier to collaborate and exchange information  Create virtual organizations where geographically dispersed people can work together using groupware  Enables electronic commerce  Problems  Eavesdropping or intrusion on communication  Tracking of communication to build a profile

Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved Transparency in a Distributed System Figure 1-2. Different forms of transparency in a distributed system (ISO, 1995).

Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved Degree of Transparency Completing hiding the distribution aspects from users is not always a good idea in a distributed system.  Attempting to mask a server failure before trying another one may slow down the system  Expecting several replicas to be always consistent could degrade performance unacceptably  For mobile and embedded devices, it may be better to expose distribution rather than trying to hide it  Signal transmission is limited by the speed of light as well as the speed of intermediate switches.

Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved Openness An open distributed system offers services according to standard rules that describe the syntax and semantics of those services.  Services are described via interfaces, which are often describe via an Interface Definition Language (IDL). Interfaces only specify syntax so semantics is left to the ambiguities of natural language.  Interoperability, Portability, Extensibility  Separating policy from mechanism

Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved Scalability Scalability can be measured against three dimensions.  Size: be able to easily add more users and resources to a system  Geography: be able to handle users and resources that are far apart  Administrative: be able to manage even if it spans independent administrative organizations Centralized versus distributed implementations.

Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved Centralized: Scalability Problems Figure 1-3. Examples of scalability limitations.

Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved Distributed Approach Characteristics of decentralized algorithms:  No machine has complete information about the system state  Machines make decisions based only on local information  Failure of one machine does not ruin the algorithm  There is no implicit assumption that a global clock exists

Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved Scaling Techniques  Hiding communication latencies: Examples would be asynchronous communication as well as pushing code down to clients (e.g. Java applets and Javascript)  Distribution: Taking a component, splitting into smaller parts, and subsequently spreading them across the system  Replication: Replicating components increases availability, helps balance the load leading to better performance, helps hide latencies for geographically distributed systems. Caching is a special form of replication.

Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved Scaling Techniques (1) Figure 1-4. The difference between letting (a) a server or (b) a client check forms as they are being filled.

Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved Scaling Techniques (2) Figure 1-5. An example of dividing the DNS name space into zones.

Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved Pitfalls when Developing Distributed Systems False assumptions made by first time developer:  The network is reliable  The network is secure  The network is homogeneous  The topology does not change  Latency is zero  Bandwidth is infinite  Transport cost is zero  There is one administrator

Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved Types of Distributed Systems  Distributed Computing Systems  Cluster Computing Systems  Grid Computing Systems  Distributed Information Systems  Transaction Processing Systems  Enterprise Application Integration  Distributed Pervasive Systems  Home Systems  Electronic Health Care Systems  Sensor Networks

Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved Cluster Computing Systems Figure 1-6. An example of a cluster computing system.

Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved Grid Computing Systems Figure 1-7. A layered architecture for grid computing systems.

Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved Transaction Processing Systems (1) Figure 1-8. Example primitives for transactions.

Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved Transaction Processing Systems (2) ACID characteristic properties of transactions:  Atomic: To the outside world, the transaction happens indivisibly.  Consistent: The transaction does not violate system invariants.  Isolated: Concurrent transactions do not interfere with each other.  Durable: Once a transaction commits, the changes are permanent.

Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved Transaction Processing Systems (3) Figure 1-9. A nested transaction.

Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved Transaction Processing Systems (4) Figure The role of a TP monitor in distributed systems.

Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved Enterprise Application Integration Figure Middleware as a communication facilitator in enterprise application integration. RPC, RMI and MOM are examples.

Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved Distributed Pervasive Systems Requirements for pervasive systems  Embrace contextual changes.  Encourage ad hoc composition.  Recognize sharing as the default.

Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved Electronic Health Care Systems (1) Questions to be addressed for health care systems:  Where and how should monitored data be stored?  How can we prevent loss of crucial data?  What infrastructure is needed to generate and propagate alerts?  How can physicians provide online feedback?  How can extreme robustness of the monitoring system be realized?  What are the security issues and how can the proper policies be enforced?

Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved Electronic Health Care Systems (2) Figure Monitoring a person in a pervasive electronic health care system, using (a) a local hub or (b) a continuous wireless connection.

Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved Sensor Networks (1) Questions concerning sensor networks:  How do we (dynamically) set up an efficient tree in a sensor network?  How does aggregation of results take place? Can it be controlled?  What happens when network links fail?

Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved Sensor Networks (2) Figure Organizing a sensor network database, while storing and processing data (a) only at the operator’s site or …

Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved Sensor Networks (3) Figure Organizing a sensor network database, while storing and processing data … or (b) only at the sensors.